Overview

Dataset statistics

Number of variables10
Number of observations60
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.9 KiB
Average record size in memory84.2 B

Variable types

Categorical6
Text1
Boolean3

Dataset

Description대구교통공사에서 운영하는 대구3호선의 승강장 정보에 대한 데이터로 철도운영기관명, 선명, 역명, 승강장번호, 상하행구분, 지상구분, 역층, 승강장연결 여부, 스크린도어 유무, 안전발판 유무의 데이터가 있습니다.
Author국가철도공단
URLhttps://www.data.go.kr/data/15041179/fileData.do

Alerts

철도운영기관명 has constant value ""Constant
선명 has constant value ""Constant
지상구분 has constant value ""Constant
승강장연결 여부 has constant value ""Constant
스크린도어 유무 has constant value ""Constant
안전발판 유무 has constant value ""Constant
상하행 is highly overall correlated with 승강장번호High correlation
승강장번호 is highly overall correlated with 상하행High correlation

Reproduction

Analysis started2023-12-12 21:25:19.304831
Analysis finished2023-12-12 21:25:19.819899
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
대구교통공사
60 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대구교통공사
2nd row대구교통공사
3rd row대구교통공사
4th row대구교통공사
5th row대구교통공사

Common Values

ValueCountFrequency (%)
대구교통공사 60
100.0%

Length

2023-12-13T06:25:19.888232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:25:19.996099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구교통공사 60
100.0%

선명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
3호선
60 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3호선
2nd row3호선
3rd row3호선
4th row3호선
5th row3호선

Common Values

ValueCountFrequency (%)
3호선 60
100.0%

Length

2023-12-13T06:25:20.113764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:25:20.231084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3호선 60
100.0%

역명
Text

Distinct30
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-13T06:25:20.427635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length4.2333333
Min length2

Characters and Unicode

Total characters254
Distinct characters73
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row건들바위
2nd row건들바위
3rd row공단
4th row공단
5th row구암
ValueCountFrequency (%)
건들바위 2
 
3.3%
공단 2
 
3.3%
학정 2
 
3.3%
팔달시장 2
 
3.3%
팔달 2
 
3.3%
팔거(국립농관원·통계청 2
 
3.3%
태전 2
 
3.3%
칠곡운암 2
 
3.3%
칠곡경대병원 2
 
3.3%
지산 2
 
3.3%
Other values (20) 40
66.7%
2023-12-13T06:25:20.801396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 10
 
3.9%
장 10
 
3.9%
성 8
 
3.1%
시 8
 
3.1%
동 8
 
3.1%
( 8
 
3.1%
) 8
 
3.1%
팔 6
 
2.4%
산 6
 
2.4%
달 6
 
2.4%
Other values (63) 176
69.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 222
87.4%
Open Punctuation 8
 
3.1%
Close Punctuation 8
 
3.1%
Decimal Number 6
 
2.4%
Uppercase Letter 6
 
2.4%
Other Punctuation 4
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 10
 
4.5%
장 10
 
4.5%
성 8
 
3.6%
시 8
 
3.6%
동 8
 
3.6%
팔 6
 
2.7%
산 6
 
2.7%
달 6
 
2.7%
구 6
 
2.7%
수 6
 
2.7%
Other values (54) 148
66.7%
Uppercase Letter
ValueCountFrequency (%)
C 2
33.3%
B 2
33.3%
T 2
33.3%
Decimal Number
ValueCountFrequency (%)
2 4
66.7%
8 2
33.3%
Other Punctuation
ValueCountFrequency (%)
· 2
50.0%
. 2
50.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 222
87.4%
Common 26
 
10.2%
Latin 6
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 10
 
4.5%
장 10
 
4.5%
성 8
 
3.6%
시 8
 
3.6%
동 8
 
3.6%
팔 6
 
2.7%
산 6
 
2.7%
달 6
 
2.7%
구 6
 
2.7%
수 6
 
2.7%
Other values (54) 148
66.7%
Common
ValueCountFrequency (%)
( 8
30.8%
) 8
30.8%
2 4
15.4%
· 2
 
7.7%
. 2
 
7.7%
8 2
 
7.7%
Latin
ValueCountFrequency (%)
C 2
33.3%
B 2
33.3%
T 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 222
87.4%
ASCII 30
 
11.8%
None 2
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 10
 
4.5%
장 10
 
4.5%
성 8
 
3.6%
시 8
 
3.6%
동 8
 
3.6%
팔 6
 
2.7%
산 6
 
2.7%
달 6
 
2.7%
구 6
 
2.7%
수 6
 
2.7%
Other values (54) 148
66.7%
ASCII
ValueCountFrequency (%)
( 8
26.7%
) 8
26.7%
2 4
13.3%
C 2
 
6.7%
B 2
 
6.7%
T 2
 
6.7%
. 2
 
6.7%
8 2
 
6.7%
None
ValueCountFrequency (%)
· 2
100.0%

승강장번호
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
1
30 
2
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 30
50.0%
2 30
50.0%

Length

2023-12-13T06:25:20.932063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:25:21.045842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 30
50.0%
2 30
50.0%

상하행
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
상행
30 
하행
30 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상행
2nd row하행
3rd row상행
4th row하행
5th row상행

Common Values

ValueCountFrequency (%)
상행 30
50.0%
하행 30
50.0%

Length

2023-12-13T06:25:21.150359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:25:21.283878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상행 30
50.0%
하행 30
50.0%

지상구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
지상
60 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지상
2nd row지상
3rd row지상
4th row지상
5th row지상

Common Values

ValueCountFrequency (%)
지상 60
100.0%

Length

2023-12-13T06:25:21.394701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:25:21.480254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지상 60
100.0%

역층
Categorical

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
3
46 
2
14 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row2

Common Values

ValueCountFrequency (%)
3 46
76.7%
2 14
 
23.3%

Length

2023-12-13T06:25:21.576786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:25:21.668717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 46
76.7%
2 14
 
23.3%

승강장연결 여부
Boolean

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size192.0 B
True
60 
ValueCountFrequency (%)
True 60
100.0%
2023-12-13T06:25:21.769590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

스크린도어 유무
Boolean

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size192.0 B
True
60 
ValueCountFrequency (%)
True 60
100.0%
2023-12-13T06:25:21.850038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

안전발판 유무
Boolean

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size192.0 B
True
60 
ValueCountFrequency (%)
True 60
100.0%
2023-12-13T06:25:21.936968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:25:22.280625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명승강장번호상하행역층
역명1.0000.0000.0001.000
승강장번호0.0001.0000.9990.000
상하행0.0000.9991.0000.000
역층1.0000.0000.0001.000
2023-12-13T06:25:22.366187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역층상하행승강장번호
역층1.0000.0000.000
상하행0.0001.0000.966
승강장번호0.0000.9661.000
2023-12-13T06:25:22.458753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
승강장번호상하행역층
승강장번호1.0000.9660.000
상하행0.9661.0000.000
역층0.0000.0001.000

Missing values

2023-12-13T06:25:19.595870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:25:19.765925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

철도운영기관명선명역명승강장번호상하행지상구분역층승강장연결 여부스크린도어 유무안전발판 유무
0대구교통공사3호선건들바위1상행지상3YYY
1대구교통공사3호선건들바위2하행지상3YYY
2대구교통공사3호선공단1상행지상3YYY
3대구교통공사3호선공단2하행지상3YYY
4대구교통공사3호선구암1상행지상2YYY
5대구교통공사3호선구암2하행지상2YYY
6대구교통공사3호선남산1상행지상3YYY
7대구교통공사3호선남산2하행지상3YYY
8대구교통공사3호선달성공원1상행지상3YYY
9대구교통공사3호선달성공원2하행지상3YYY
철도운영기관명선명역명승강장번호상하행지상구분역층승강장연결 여부스크린도어 유무안전발판 유무
50대구교통공사3호선팔거(국립농관원·통계청)1상행지상3YYY
51대구교통공사3호선팔거(국립농관원·통계청)2하행지상3YYY
52대구교통공사3호선팔달1상행지상2YYY
53대구교통공사3호선팔달2하행지상2YYY
54대구교통공사3호선팔달시장1상행지상3YYY
55대구교통공사3호선팔달시장2하행지상3YYY
56대구교통공사3호선학정1상행지상3YYY
57대구교통공사3호선학정2하행지상3YYY
58대구교통공사3호선황금1상행지상3YYY
59대구교통공사3호선황금2하행지상3YYY